Safe Reasoning Over Ontologies
| dc.creator | Grabarnik, Genady | |
| dc.creator | Kershenbaum, Aaron | |
| dc.date | 2009-04-01 | |
| dc.date.accessioned | 2026-07-07T12:59:08Z | |
| dc.date.available | 2026-07-07T12:59:08Z | |
| dc.description | As ontologies proliferate and automatic reasoners become more powerful, the problem of protecting sensitive information becomes more serious. In particular, as facts can be inferred from other facts, it becomes increasingly likely that information included in an ontology, while not itself deemed sensitive, may be able to be used to infer other sensitive information. We first consider the problem of testing an ontology for safeness defined as its not being able to be used to derive any sensitive facts using a given collection of inference rules. We then consider the problem of optimizing an ontology based on the criterion of making as much useful information as possible available without revealing any sensitive facts. | |
| dc.identifier | https://arxiv.org/abs/0904.0228 | |
| dc.identifier | http://arxiv.org/abs/0904.0228 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/225480 | |
| dc.subject | Artificial Intelligence | |
| dc.subject | Data Structures and Algorithms | |
| dc.title | Safe Reasoning Over Ontologies | |
| dc.type | text |